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Eppo
Next-generation A/B testing and feature flagging platform.
What it does
Automates experiment analysis and metric governance directly on top of modern data warehouses. Manages feature flags and targeted rollouts for engineering and product teams. Performs marketing incrementality tests and causal inference evaluations. Provides deep personalization and AI model evaluation capabilities for data-driven organizations.
Why it works
Direct connection to the modern data warehouse eliminates redundant data storage and pipelines. Rigorous statistical engine ensures high power and minimizes false positives in testing results. Unified workflows combine feature flagging and experiment analysis into a single interface. Scales effectively from mid-market startups to high-volume enterprise tech companies.
Category: Business & Operations
Team Size: 26-100
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As of 2026
Business & Operations
Revenue: $10M-100M ARR
Next-generation A/B testing and feature flagging platform.
Overview
Eppo is a modern experimentation and feature management platform designed to help data and product teams run reliable A/B tests. Leveraging the modern data stack, it connects directly to data warehouses to deliver automated experiment analysis and metric governance. The platform streamlines rollouts while minimizing heavy manual data engineering work. Enterprises use Eppo to scale decision-making velocity and align product changes with core business revenue.
Funding status: Acquired
Revenue source: Subscriptions
Customer type: B2B
Pricing: Enterprise
Tech stack: Cloud infrastructure, Modern data stack, REST APIs, TypeScript
Platform: Web
Integrations: Snowflake, BigQuery, Databricks, Redshift, Amplitude, Mixpanel, Slack, GitHub
Founder story
Eppo was founded in 2021 by Chetan Sharma in San Francisco, United States. Having experienced the challenges of scaling internal experimentation tools at leading tech companies, the founder built Eppo to democratize enterprise-grade A/B testing. Backed by major venture capital investors, the company has grown into a key player in the data analytics and experimentation space.
What it does
- Automates experiment analysis and metric governance directly on top of modern data warehouses
- Manages feature flags and targeted rollouts for engineering and product teams
- Performs marketing incrementality tests and causal inference evaluations
- Provides deep personalization and AI model evaluation capabilities for data-driven organizations.
Who it's for
- Product Managers
- Data Analysts and Scientists
- Software Engineers
- Growth Marketing Teams
Why it works
- Direct connection to the modern data warehouse eliminates redundant data storage and pipelines
- Rigorous statistical engine ensures high power and minimizes false positives in testing results
- Unified workflows combine feature flagging and experiment analysis into a single interface
- Scales effectively from mid-market startups to high-volume enterprise tech companies.
Growth strategies
- Direct B2B enterprise sales targeting high- growth technology companies
- Product- led growth through seamless integration with cloud data warehouses like Snowflake and BigQuery
- Thought leadership in modern experimentation metrics and causal inference frameworks
- Strategic partnerships across the modern data stack ecosystem
Alternatives
Comparison overview
- [Eppo computes experiment results directly within the user's data warehouse for transparent metric governance n/][Alternative platforms like LaunchDarkly focus heavily on feature management with separate proprietary analytics infrastructure n/]